{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "score = np.random.randint(1,44,(5,5))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['35', '10', '25', '35', '38'],\n",
       "       ['33', '30', '不及格', '25', '41'],\n",
       "       ['27', '11', '10', '29', '26'],\n",
       "       ['14', '41', '不及格', '35', '31'],\n",
       "       ['不及格', '26', '13', '不及格', '不及格']], dtype='<U11')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(score<10, '不及格', score)"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "11f1dc213e07634baa4c5c321dec03c05dafae643c50f20e6d1a492290c05dc2"
  },
  "kernelspec": {
   "display_name": "Python 3.9.7 64-bit",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
